



'''simple docstring'''






import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin

@require_jieba
class 				a__(   lowerCamelCase__						,					unittest.TestCase      ):
    lowercase__					=       CpmAntTokenizer
    lowercase__					=       False







    def      lowercase_			( self					:    Dict      ):
      super().setUp()

      a		:   Dict	  =	[
          '<d>',
          '</d>',
          '<s>',
          '</s>',
          '</_>',
          '<unk>',
          '<pad>',
          '</n>',
          '我',
          '是',
          'C',
          'P',
          'M',
          'A',
          'n',
          't',
      ]
      a		:   Tuple	  =	os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['vocab_file']      )
      with open(self.vocab_file		,     'w'		,     encoding='utf-8'      ) as vocab_writer:
        vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]      )      )







    @tooslow
    def      lowercase_			( self					:    int      ):
      a		:   Any	  =	CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b'      )
      a		:   List[str]	  =	'今天天气真好！'
      a		:   Optional[Any]	  =	['今天', '天气', '真', '好', '！']
      a		:   Union[str, Any]	  =	tokenizer.tokenize(__snake_case      )
      self.assertListEqual(__snake_case		,     __snake_case      )
      a		:   Any	  =	'今天天气真好！'
      a		:   str	  =	[tokenizer.bos_token] + tokens

      a		:   Dict	  =	[6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case      )		,     __snake_case      )

      a		:   Union[str, Any]	  =	tokenizer.decode(__snake_case      )
      self.assertEqual(__snake_case		,     __snake_case      )




'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:   List[str]					=		logging.get_logger(__name__)

lowerCAmelCase:   Union[str, Any]					=		{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """lilt"""







    def __init__( self					:    str		,     __snake_case					:    Dict=3_05_22		,     __snake_case					:    int=7_68		,     __snake_case					:    Union[str, Any]=12		,     __snake_case					:    Optional[Any]=12		,     __snake_case					:    Dict=30_72		,     __snake_case					:    Tuple="gelu"		,     __snake_case					:    Dict=0.1		,     __snake_case					:    List[Any]=0.1		,     __snake_case					:    List[str]=5_12		,     __snake_case					:    List[str]=2		,     __snake_case					:    str=0.02		,     __snake_case					:    Dict=1e-1_2		,     __snake_case					:    int=0		,     __snake_case					:    Any="absolute"		,     __snake_case					:    Tuple=None		,     __snake_case					:    Tuple=4		,     __snake_case					:    List[str]=10_24		,     **__snake_case					:    Union[str, Any]		,     ):
      super().__init__(pad_token_id=__snake_case		,     **__snake_case      )

      a		:   str	  =	vocab_size
      a		:   Optional[Any]	  =	hidden_size
      a		:   Union[str, Any]	  =	num_hidden_layers
      a		:   Tuple	  =	num_attention_heads
      a		:   Optional[Any]	  =	hidden_act
      a		:   Union[str, Any]	  =	intermediate_size
      a		:   Optional[Any]	  =	hidden_dropout_prob
      a		:   Tuple	  =	attention_probs_dropout_prob
      a		:   str	  =	max_position_embeddings
      a		:   Any	  =	type_vocab_size
      a		:   Union[str, Any]	  =	initializer_range
      a		:   int	  =	layer_norm_eps
      a		:   Any	  =	position_embedding_type
      a		:   Any	  =	classifier_dropout
      a		:   str	  =	channel_shrink_ratio
      a		:   Optional[Any]	  =	max_ad_position_embeddings